Bayesian methodsBayesian / computational

Spatial Bayesian Inference

Spatial Bayesian inference applies Bayesian hierarchical modeling to data indexed by geographic location. By placing structured spatial priors on location-specific random effects, the model borrows information from neighboring regions or nearby points, producing smooth, uncertainty-quantified maps of any spatially varying outcome — disease rates, pollution levels, species abundance, or environmental risk.

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Sources

  1. Banerjee, S., Carlin, B. P. & Gelfand, A. E. (2015). Hierarchical Modeling and Analysis for Spatial Data (2nd ed.). CRC Press. ISBN: 978-1439819173
  2. Besag, J., York, J. & Mollie, A. (1991). Bayesian image restoration, with two applications in spatial statistics. Annals of the Institute of Statistical Mathematics, 43(1), 1-20. DOI: 10.1007/BF00116466

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Referenced by

ScholarGateSpatial Bayesian Inference (Spatial Bayesian Inference). Retrieved 2026-06-04 from https://scholargate.app/en/bayesian/spatial-bayesian-inference